35 citations · 56 across the 11 of their papers we have counts for
6 papers · 1 filter
The Two Faces of AI in Green Mobile Computing: A Literature Review
Wander Siemers, June Sallou, Luís Cruz
Artificial intelligence is bringing ever new functionalities to the realm of mobile devices that are now considered essential (e.g., camera and voice assistants, recommender system…
Batching for Green AI -- An Exploratory Study on Inference
Tim Yarally, Luís Cruz, Daniel Feitosa +2
The batch size is an essential parameter to tune during the development of new neural networks. Amongst other quality indicators, it has a large degree of influence on the model's…
Green Runner: A tool for efficient model selection from model repositories
Jai Kannan, Scott Barnett, Anj Simmons +2
Deep learning models have become essential in software engineering, enabling intelligent features like image captioning and document generation. However, their popularity raises co…
Towards Understanding Machine Learning Testing in Practise
Arumoy Shome, Luis Cruz, Arie van Deursen
Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive…
Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI
Tim Yarally, Luís Cruz, Daniel Feitosa +2
Modern AI practices all strive towards the same goal: better results. In the context of deep learning, the term "results" often refers to the achieved accuracy on a competitive pro…
A Systematic Review of Green AI
Roberto Verdecchia, June Sallou, Luís Cruz
With the ever-growing adoption of AI-based systems, the carbon footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to hold themselves acco…